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"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "4cd1da0e",
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2\n",
"import pandas as pd\n",
"import numpy as np\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"from synthetic_task.plot_results import load_comp_grad_results_metrics, plot_comp_grad_metrics_vs_iter_by_ydim"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "6f2b2dea",
"metadata": {},
"outputs": [],
"source": [
"sns.set_theme(style=\"whitegrid\", context=\"talk\")\n",
"palette = sns.color_palette()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "d24a0bbc",
"metadata": {},
"outputs": [],
"source": [
"batch_size = 8\n",
"COMP_GRAD_DIR = f\"../synthetic_results_compare_grad_{batch_size}\"\n",
"\n",
"METHODS = [\n",
" \"ffocp_eq\",\n",
"]\n",
"METHODS_LEGEND = {\n",
" \"ffocp_eq\": \"FFOCP\",\n",
"}\n",
"\n",
"method_order = [METHODS_LEGEND[m] for m in METHODS]\n",
"\n",
"METHODS_STEPS = [method+\"_steps\" for method in METHODS]\n",
"\n",
"df = load_comp_grad_results_metrics(\n",
" base_dir=COMP_GRAD_DIR,\n",
" methods=METHODS_STEPS,\n",
" methods_legend=METHODS_LEGEND,\n",
" parse_backwardTol=True,\n",
")\n",
"\n",
"df[\"method\"] = pd.Categorical(df[\"method\"], categories=method_order, ordered=True)\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "af45fabd",
"metadata": {},
"outputs": [],
"source": [
"markers = [\"o\", \"s\", \"D\", \"^\", \"v\", \"x\", \"P\", \"s\"]\n",
"markers_dict = {m: markers[i] for i, m in enumerate(method_order)}\n",
"plot_comp_grad_metrics_vs_iter_by_ydim(\n",
" df,\n",
" plot_path=COMP_GRAD_DIR,\n",
" plot_name_tag=\"grad\",\n",
" filter_method=\"FFOCP\",\n",
" filter_backwardTol=1e-5,\n",
" cosine_ylim=(0.5, 1.0),\n",
" legend_ncol=4,\n",
")\n",
"\n",
"# if this not work, try decrease lr."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3cb8e08c",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "4128687f",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "rl",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.14"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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